ATLANTIC CAMTRAPS - GRÁFICOS

library(here)

## here() starts at D:/git/atlantic-series/ATLANTIC_CAMTRAP

library(ggplot2)
library(forcats)
library(RColorBrewer)

DESCRIÇÃO

Gráficos para o datapaper Atlantic-Camtraps. Adaptado e organizado a partir da primeira versão criada por Renata Muylaert.

GRUPO DE TRABALHO

pH Fernando Lima, D.Sc.
RM Renata Muylaert, D.Sc.
MR Milton Ribeiro, D.Sc.

NOTAS (README)

ADICAO DE COMENTARIOS: Corpo do Texto: insira suas iniciais entre ** e depois os comentarios: e.g. **pH** blablabla Código:

Data prep

####Select species and effort data

data <- read.csv(here("data", "splist_filtered_2017_04d24.csv"), sep = ",")
ef <- read.csv(here("data", "effort.txt"), sep="\t")

####Ordenando data por ordem e por FO:

data <- data[order(data$fo),]

str(data)

## 'data.frame':    47 obs. of  11 variables:
##  $ sp_id      : int  1032 1038 1022 1078 1079 1028 1035 1080 1081 1013 ...
##  $ class      : Factor w/ 1 level "Mammalia": 1 1 1 1 1 1 1 1 1 1 ...
##  $ order      : Factor w/ 8 levels "Artiodactyla",..: 3 3 2 8 8 2 3 8 8 2 ...
##  $ family     : Factor w/ 17 levels "Canidae","Caviidae",..: 5 5 11 8 8 14 5 8 8 1 ...
##  $ genus      : Factor w/ 36 levels "Cabassous","Canis",..: 1 27 7 4 6 26 10 31 31 30 ...
##  $ species    : Factor w/ 47 levels "albiventris",..: 43 23 10 36 31 15 34 20 45 44 ...
##  $ species.1  : Factor w/ 47 levels "Cabassous tatouay",..: 2 36 8 5 7 35 14 41 42 40 ...
##  $ iucn_status: Factor w/ 5 levels "DD","IN","LC",..: 3 5 3 5 3 3 3 3 3 4 ...
##  $ sp_code1   : Factor w/ 47 levels "Caba_tato","Caba_unic",..: 2 36 8 5 7 35 14 41 42 40 ...
##  $ sp_code    : Factor w/ 47 levels "Caba_tato","Caba_unic",..: 2 36 8 5 7 35 14 41 42 40 ...
##  $ fo         : num  0.00694 0.00694 0.01389 0.01389 0.01389 ...

unique(data$sp_id)

##  [1] 1032 1038 1022 1078 1079 1028 1035 1080 1081 1013 1012 1023 1011 1074 1026
## [16] 1019 1051 1014 1055 1008 1004 1037 1006 1025 1002 1031 1053 1003 1052 1021
## [31] 1017 1039 1068 1007 1020 1073 1040 1056 1015 1016 1072 1029 1009 1024 1010
## [46] 1027 1034

head(data)

##    sp_id    class     order         family      genus     species
## 28  1032 Mammalia Cingulata    Dasypodidae  Cabassous  unicinctus
## 32  1038 Mammalia Cingulata    Dasypodidae Priodontes     maximus
## 19  1022 Mammalia Carnivora     Mephitidae  Conepatus      chinga
## 44  1078 Mammalia  Rodentia Erethizontidae  Chaetomys subspinosus
## 45  1079 Mammalia  Rodentia Erethizontidae    Coendou prehensilis
## 25  1028 Mammalia Carnivora    Procyonidae      Potos      flavus
##                species.1 iucn_status  sp_code1   sp_code      fo
## 28  Cabassous unicinctus          LC Caba_unic Caba_unic 0.00694
## 32    Priodontes maximus          VU Prio_maxi Prio_maxi 0.00694
## 19      Conepatus chinga          LC Cone_chin Cone_chin 0.01389
## 44 Chaetomys subspinosus          VU Chae_subs Chae_subs 0.01389
## 45   Coendou prehensilis          LC Coen_preh Coen_preh 0.01389
## 25          Potos flavus          LC Poto_flav Potu_flav 0.02083

###FIGURE 01 - MAP

Generated in ArcGis by Fernando Lima

Fig. 1. Distribution of the camera trap surveys of medium and large terrestrial mammal communities within the Atlantic Forest extent. Gray shows the Atlantic Forest extent with remaining forest patches in green (sensu Ribeiro et al. 2009). Blue dots show the geographic locations of studies.

###FIGURA 02 - SUNBURST

Esta figura foi feita no Excel, utilizando a função sunburst

Fig. 2. Taxonomic information levels of medium and large terrestrial mammal species recorded in camera trap surveys within the Atlantic Forest. Only species considered well detected by camera traps are listed. From the 83 species reported in the database, 8 are not listed because the identification is at genera level. Another 28 species are not listed because they were considered opportunistic records of species not usually detected by camera traps (primates, bats, small rodents, and small marsupials).

###FIGURA 03 - FREQUENCIA DE OCORRENCIA

RM Demanda: Casar as cores com o sunburst!
pH Eu mudei a paleta de cores. Inseri os codigos RGB para usar igual no Excel.

fct_rev(fct_infreq(factor(data$species.1)))

##  [1] Cabassous unicinctus      Priodontes maximus       
##  [3] Conepatus chinga          Chaetomys subspinosus    
##  [5] Coendou prehensilis       Potos flavus             
##  [7] Dasypus septemcinctus     Sphiggurus insidiosus    
##  [9] Sphiggurus villosus       Speothos venaticus       
## [11] Lycalopex gymnocercus     Conepatus semistriatus   
## [13] Chrysocyon brachyurus     Dasyprocta leporina      
## [15] Lontra longicaudis        Panthera onca            
## [17] Lepus europaeus           Felis catus              
## [19] Myrmecophaga tridactyla   Tayassu pecari           
## [21] Mazama nana               Euphractus sexcinctus    
## [23] Sus scrofa                Galictis cuja            
## [25] Mazama americana          Cabassous tatouay        
## [27] Tapirus terrestris        Mazama gouazoubira       
## [29] Sylvilagus brasiliensis   Puma yagouaroundi        
## [31] Leopardus wiedii          Didelphis albiventris    
## [33] Hydrochoerus hydrochaeris Pecari tajacu            
## [35] Puma concolor             Dasyprocta azarae        
## [37] Didelphis aurita          Tamandua tetradactyla    
## [39] Leopardus pardalis        Leopardus guttulus       
## [41] Cuniculus paca            Procyon cancrivorus      
## [43] Canis familiaris          Eira barbara             
## [45] Cerdocyon thous           Nasua nasua              
## [47] Dasypus novemcinctus     
## 47 Levels: Tayassu pecari Tapirus terrestris ... Cabassous tatouay

colnames(data)[3]<-paste("Order")
getwd()

## [1] "D:/git/atlantic-series/ATLANTIC_CAMTRAP/src"

p<- ggplot(data, aes(x=reorder(species.1, -fo) , y=fo, fill=Order))+
    geom_bar(width=0.8,stat="identity", color = "black", position="stack", size =0.3) + #dimgray
    #, size = 1, shape = 1
    theme_bw() +
    #facet_wrap(~order)+
    xlab("Species") + 
    ylab("Frequency of occurrence")+
    theme(legend.position="top")+
    theme(axis.text.x = element_text(angle=45, # pH # mudei de 90 para 45
    vjust=1,
    hjust = 1, # pH # adicionei
    family="Times", face="italic", colour="black", size=rel(0.9)))+
    geom_text(aes(label=iucn_status), position=position_dodge(width=0.7), size=3, colour="black", vjust=-0.25)+
    theme(plot.margin = unit(c(0.5,0.5,0.5,1),"cm"))

cores<-c("indianred1" , # pH # artiodactyla mudar para indianred #cd5c5c rgb(205,92,92)
    "coral",  # pH # carnivora #ff7f50 rgb(255,127,80)
    "orchid" , # pH # cingulata mudar para orchid 
    "burlywood", # pH # didelphimorphia #deb887 rgb(222,184,135)
    "khaki", # pH # lagomorpha mudar para khaki #f0e68c rgb(240,230,140)
    "darkseagreen", # pH #  perisodactyla mudar para darkseagreen #8fbc8f rgb(143,188,143)
    "mediumaquamarine", # pH # pilosa #66cdaa rgb(102,205,170)   
    "dodgerblue" ) # pH #  rodentia mudar para dodger blue #1e90ff rgb(30,144,255)
    #png(filename= "Fig3_v19.png", res= 300,  height= 16, width=26, unit="cm")
    #p+ scale_fill_manual(values=cores)
    #dev.off()

# pH #  mesmo que acima, mas usando os codigos
    
    cores<-c("#cd5c5c" , # pH # artiodactyla mudar para indianred #cd5c5c rgb(205,92,92)
             "#ff7f50",  # pH # carnivora #ff7f50 rgb(255,127,80)
             "#da70d6" , # pH # cingulata mudar para orchid #da70d6 rgb(218,112,214)
             "#deb887", # pH # didelphimorphia #deb887 rgb(222,184,135)
             "#f0e68c", # pH # lagomorpha mudar para khaki #f0e68c rgb(240,230,140)
             "#8fbc8f", # pH #  perisodactyla mudar para darkseagreen #8fbc8f rgb(143,188,143)
             "#66cdaa", # pH # pilosa #66cdaa rgb(102,205,170)   
             "#1e90ff" ) # pH # rodentia mudar para dodger blue #1e90ff rgb(30,144,255)
    
    #png(filename= "Fig3_v20.png", res= 300,  height= 16, width=26, unit="cm")
    #p+ scale_fill_manual(values=cores)
    #dev.off()

Fig. 3. Distribution of frequencies of occurrence of the main species evaluated in ATLANTIC-CAMTRAPS, and their status in the 2017 IUCN Red list of threatened species. LC = least concern, NT = near threatened, VU = vulnerable, EN = endangered, CR = critically endangered, DD = data deficient, and IN = invasive species (not an IUCN category).

FIGURA 04 - MAPA

O mapa foi feito no ArcMap

Fig. 4. Distribution of taxonomic richness and sampling effort across Atlantic Forest sites where camera traps were used for sampling of medium and large terrestrial mammal species. Opportunistic records (see the text) were removed from this analysis.